Calcium has been one of the most versatile biological messengers in a cell, playing critical roles in regulating the cell's functions. In particular, the transient change of calcium concentration in cardiac muscle cells (myocytes) forms the basis of cell-wide contraction that eventually results in the whole heart contraction. Studying calcium signaling in cardiac myocytes is thus a fundamental research topic in understanding the excitation-contraction (E-C) coupling in the cells and ultimately revealing the microscopic mechanism of heart disease. The main goal of the present proposal is to utilize three-dimensional (3D) electron microscopic (EM) images and mathematical simulation techniques to explore image-based modeling of calcium signaling in ventricular myocytes to achieve a realistic understanding of the microscopic environment of heart disease. The specific aims of the proposed studies are: (A) Constructing realistic geometric models from advanced 3D EM imaging data. Efficient computational approaches of image processing, analysis and geometric modeling will be developed and implemented to extract the sub-cellular structures of interest and to construct high-fidelity, high-quality surface and volumetric meshes that will be used in the subsequent mathematical simulation. (B) Characterizing calcium signaling using both stochastic and deterministic methods. We shall explore how unitary calcium release events (i.e. calcium sparks) are formed within/around a single CRU using the Monte Carlo method. Anatomical models extracted from 3D EM images will be used to specify the simulation domains. In addition, finite element (deterministic) methods will be employed to investigate the calcium signaling (waves) across CRUs, where the simulation domains will be specified with realistic geometric models extracted from advanced 3D EM images. Both normal and diseased ventricular myocytes will be investigated. (C) Developing a graphical user interface (GUI) to streamline anatomical modeling and visualization of biomedical images. A user-friendly GUI will be created to encapsulate all the computational modules for image processing, feature extraction, and mesh generation. This toolkit is made to streamline multiple computational processes from 2D/3D images to 3D anatomical models and will be made available to the biomedical community. PUBLIC HEALTH RELEVANCE: Heart failure has been one of the leading causes of human deaths in many countries including the United States. The prevalence of this disease is largely due to our lack of accurate understanding of excitation-contraction (E-C) coupling in cardiomyocytes. Computer and mathematical modeling of calcium signaling has been an important way to achieve this goal. The proposed study will enable us to model calcium signaling using the structural information extracted from the 3D imaging data, which would provide a more realistic and accurate understanding of the mechanism of heart disease.